Prioritizing research: evaluation of a portfolio management approach in clinical

描述(由申请人提供)：目前使用的所有医学干预措施中，只有不到一半得到了临床证据的支持。尽管每年拨出超过110亿美元用于支持临床研究，但联邦政府对医学研究的资助缺乏一个协调的系统来确定优先顺序和分配资源，以有效地解决这些重要的知识差距。因此，如果有限的公共资金要以可能对公共卫生产生最大影响的方式使用，那么一个协调的系统来优先处理最有希望的临床研究是至关重要的。投资组合管理是一种系统的决策方法，在私营部门被广泛用于通知和管理研究投资。这项建议的总体目标是确定项目组合管理框架是否可以提高在大型癌症背景下选择公共资助的研究并对其进行优先排序的效率 临床试验合作组。在公共研究环境中实施这种框架的关键挑战是难以定义和有效地估计绩效的两个关键衡量标准，即预期失败风险和拟议研究的预期社会回报。因此，这项建议的目的是开发和评估风险和回报的量化指标，这些指标适合于公共资助的临床试验环境，并与利益相关者相关并被利益相关者接受。我们将开发一个统计模型来预测临床试验失败的风险，根据试验启动前可用的试验水平变量，临床试验失败的风险被定义为没有招募足够数量的患者，因此无法告知临床实践模式的试验。我们将使用信息价值(VOI)分析来量化拟议研究的社会回报，并将开发一个过程，使用一种相对较新的技术-最小建模VOI-快速有效地生成这些估计。最后，我们将评估最近审查的临床试验提案样本的风险和回报指标，以说明投资组合管理框架如何在癌症临床试验合作小组环境中提高资金决策的效率。制定风险和回报措施将为决策者提供有关他们审查的研究建议的宝贵信息，并帮助他们作出更有系统和更有效的筹资决定。如果成功，该项目可以为医学研究组织和资助机构提供一种新的优先模式，并最终有助于最大限度地发挥有限研究资金对公共卫生的影响。

DESCRIPTION (provided by applicant): Fewer than half of all medical interventions in use today are supported by clinical evidence. Despite allocating more than $11 billion each year to support clinical research, federal funding for medical research lacks a coordinated system for prioritizing and allocating resources to efficiency address these important knowledge gaps. Thus a coordinated system to prioritize the most promising clinical research is critical if limited publc funds are to be used in ways that are likely to have the greatest impact on public health. Portfolio management is a systematic approach to decision-making that is widely used in the private sector to inform and manage research investments. The overall objective of this proposal is to determine whether a portfolio management framework can improve the efficiency of selecting and prioritizing publicly funded research studies within the setting of a large cancer clinical trials cooperative group. The key challenge to implementing such a framework in the public research setting is the difficultly in defining and efficiently estimating two key measures f performance the expected risk of failure and the expected societal return from the proposed research study. The aims of this proposal are therefore to develop and evaluate quantitative metrics of risk and return that are appropriate for the publicly funded clinical trial setting and relevant to and accepted by stakeholders. We will develop a statistical model to predict the risk of a clinical trial failure, defined as a trial that does not enroll a sufficient number of patient and consequently is unable to inform clinical practice patterns, based on trial-level variables available before the trial is launched. We will quantify the societal return of the proposed studie using Value of Information (VOI) analyses and will develop a process for rapidly and efficiently generating these estimates using a relatively new technique, minimal modeling VOI. Lastly, we will estimate measures of risk and return for a sample of recently reviewed clinical trial proposals to illustrate how a portfolio management framework can improve the efficiency of funding decisions within a cancer clinical trials cooperative group setting. Developing measures of risk and return will provide decision makers with valuable information on the study proposals they review and help them make more systematic and efficient funding decisions. If successful, this project could provide a novel prioritization paradigm for medical research organizations and funding agencies, and ultimately help maximize the public health impact of limited research funds.